In many businesses today, managers struggle to minimize employee labor costs. In deciding how many employees are necessary for daily business operations, managers constantly balance competing and conflicting business needs. Take, for example, a manager of a retail store. The manager may want to minimize the number of point of sale (POS) cashiers. Obviously, employing fewer POS cashiers results in reduced labor costs. However, managers risk aggravating or irritating customers when checkout lines and checkout times become too long due to a shortage of POS cashiers. Irritated customers may not return, resulting in lower business revenues. Conversely, if a manager uses too many POS cashiers, labor costs accrue unnecessarily when relatively few customers check out and some cashiers remain idle.
Another example of conflicting business needs that challenge managers involves staffing warehouse, or storage area, employees. Managers must select a minimum number of workers to unload product shipments from freight carriers, such as freight trucks. Similar to the POS cashier dilemma, the manager must strike a balance between the number of warehouse workers and the arrival of product shipments. If the manager employs too few warehouse workers, freight trucks may wait unnecessarily long periods of time resulting in increased freight charges. Alternatively, employing too many warehouse workers drives up labor costs when no product shipments are being unloaded and the warehouse workers sit idle. Choosing an optimal number of POS cashiers and selecting an optimal number of warehouse workers are only two examples of the challenges that managers face in minimizing employee labor costs. Similar challenges are readily found in all types of businesses.
Managers often avoid problems of understaffing by erring on the side of caution and employing a potentially excessive number of employees. Utilizing an excessive number of employees may work relatively well but this method has a major drawback, that drawback being unnecessarily high business operating costs.
As an alternative to overstaffing, managers may strive to minimize labor costs by diligently comparing real-time employee workloads with corresponding real-time workload requirements and making employee staffing decisions accordingly. For example, a store manager may notice that the lengths of POS lines for store customers waiting to make their final purchases have become unacceptably long due to an insufficient number of POS cashiers. The store manager may respond by summoning other store employees, via a store pager or some other means, to come to the POS lines and serve as cashiers. Conversely, the store manager may notice that several cashiers are sitting idle, due to too few store customers checking out. The manager may respond by deploying idle cashiers to other areas of the store where the workload is greater. This method of continually adjusting the number of employees at POS stations is merely one example. In a similar example, managers may monitor warehouse activities and summon more employees to either load or unload products to or from freight carriers, depending on product shipping demands.
Dispatching POS and warehouse employees in this manner has several drawbacks. First, the effectiveness of this method depends on the effectiveness of the manager. If the manager is inefficient, this solution will also be inefficient. Second, this method requires constant manager attention. If the manager needs to attend to other business matters, the POS lines may grow unnoticed and irritate customers. Similarly, if the manager attends to other matters, the store environment may change which will cause POS lines to grow unnoticed and irritate customers by increasing their wait time for length of service. Third, this method stifles businesses wanting to decrease managerial labor costs. Similar to minimizing the number of lower skilled store employees, business owners prefer to minimize the labor costs of managers as well and staff only the minimal number of managers necessary to effectively operate the business. Unfortunately, this method generally requires increasing the number of managers, not decreasing it.
As another alternative solution, some businesses use POS transaction data and warehouse transaction data to analyze historical business needs. Using this historical transaction data, collected from such sources as item universal product code (UPC) data on products sold or received, a manager may statically analyze and predict labor requirements for a business. The manager may make staffing decisions based on these analyses. Similar to the other methods, current utilization of item UPC data requires continual or periodic manager involvement for dispatching employees to avoid labor shortfalls, such as would be the case when several checkout lines become very long despite staffing according to the analyses.
Although using historical data for predicting labor requirements has decreased labor costs and improved profits, this method also has many drawbacks. Again, the effectiveness of this solution depends on the experience and effectiveness of the manager analyzing the data and making the staffing decisions. Additionally, past data do not always accurately predict future employee labor requirement trends. One example where past data do not accurately predict future trends would be for a business that is growing. Past sales for a growing business may inadequately predict future labor requirements, with booming sales and increased warehouse shipments. Additionally, this solution is static, dependent on past data, and may not adequately address sudden dynamic increases in customer purchases or warehouse shipments.
What is needed, therefore, is a way to dynamically, efficiently, and automatically dispatch employees to locations of increased business activities. Locating, dispatching, and redeploying employees in a dynamic manner can result in higher worker productivity, improved shopping experience for customers resulting in greater customer satisfaction, and potentially lower labor costs.